I have noticed that the autoplot function in OpenStreetMaps seems to change the x,y axis scale in a strange way. Contrast the map produced through ggmap:
test1=get_map(location=c(31.00302,-4.27480,41.84012,4.291),source="osm")
ggmap(test1)
and the map created by OpenStreetMap's ggplot2 compatible plotting function:
UL=c(4.29100,31.00302)
LR=c(-4.27480,41.84012)
test2=openmap(UL,LR,type="osm")
autoplot(test2)
These two should be the same, but the map produced by autoplot has longitude and latitude coordinates multiplied by 100,000. How do I make it so that autoplot does not multiply everything by 100,000?
(Just renaming everything is not sufficient. I need the underlying coordinate system to reflect the numbers used above.)
Thank You.
I needed to change the projection to a long/lat projection. This was accomplished by:
test2=openproj(test2, projection = "+proj=longlat")
Related
I have gone through few tutorials and answers here in stackoverflow such as:
Overlap image plot on a Google Map background in R or
Plotting contours on an irregular grid or Geographical heat map of a custom property in R with ggmap or How to overlay global map on filled contour in R language or https://blog.dominodatalab.com/geographic-visualization-with-rs-ggmaps/
They either don't serve my purpose or consider the density of the data to create the image.
I am looking for a way to plot contour on a map of a certain data, and would expect the image to look something like this:
or something like this taken from https://dsparks.wordpress.com/2012/07/18/mapping-public-opinion-a-tutorial/:
I have a data here that gives a contour plot like this in plot_ly but i want this over the map given by latitudes and longitudes.
Please guide me on how this can be done. Any links to potential answers or codes would be helpful.
Ok I did some digging and figured that to plot the data -which in this case are point values randomly distributed across the Latitude and Longitude, one has to make it continuous instead of the discreetly distributed one. To do this I interpolated the data to fill in the gaps, this method is given in Plotting contours on an irregular grid and then take it from there. Now the interpolation here is done using a linear regression, one can use other methods such as IDW, Kriging, Nearest Neighbourhood etc for which R-packages are easily available. These methods are widely used in climatology and topographic analysis. To read more about interpolation methods see this paper.
I have a dense scatter plot on a map (produced using Python, matplotlib, and basemap). Here is a part of the image:
I'd like to solve the overlap problem. I think the way to do this is to combine this simple lat/lon coordinate mapping with the technique I often see implemented in those "spring-loaded" network (social, not computer) graphs.
Is there a simple existing algorithm to auto-magically move these points so that they are not overlapping? If so, I can easily than add a small line from each point to its the correct lat/lon coordinate where it is currently located.
Note: Hexbin and heatmap is not a solution since the discrete values are important and should not be compromised.
Here is what I need: I have an image and want to plot on specific rectangle-shaped parts of it (e.g., imagine having a picture of a chessboard and wanting to fill every square with a different color). I would like to be able to easily specify the coordinates for these parts and take these coordinates into R for plotting.
I don't have any experience with making such plots. I've thought of simply inserting an image into a plot with rasterImage (), then plotting with polygon (), but the task of setting up the coordinates for the polygon function seemed too time consuming - hence the question above.
If you have any better ideas than using a set of coordinates for the polygon function, please share. Any leads or packages suggestions would also be helpful.
thank you. Marko.
I just discovered ggmap and I've been playing around with plotting earthquake data from the USGS. I get the data in the form of Lat and Lon, depth and magnitude. I can easily plot the earthquakes as points with different colors based on depth but what I would like to do is take that depth data (just a single number) and generate contours to overlay on the map.
This seems like it should be MUCH more simple than the "Houston Crime" example I keep coming up on since I'm not doing any statistical "density" calculation or anything like that. Basically it's just a contour map on top of the google map of an area.
How do I do this (Presumably) simple, simple thing?
Thanks!
The problem of plotting a 3D surface using only a small sample of unequally spaced lat/long points and a height z (or equivalent) variable is non-trivial -- you have to estimate the values of z for all of the lat-long grid coordinates you do not have, for example using loess() or kriging to create a smooth surface.
Take a look at Methods for doing heatmaps, level / contour plots, and hexagonal binning, case #5. For a geoR example see http://www4.stat.ncsu.edu/~reich/CUSP/Ordinary_Kriging_in_R.pdf
I created a network graph from data on flows between US states. For each vertex, I have the lat/long of the state.
I am hoping to recreate a network kind of graph that shows the edges, except that I set the location of each vertex to be their geographic position and have a state boundary map in the background.
I am using to igraph to create my network. There have been some cool mapping examples in ggplot2, so I am wondering if that is an option. I believe I have seen similar options using Pajek, but I am hoping to stay within R.
maps in ggplot2
Any ideas/insight would be appreciated.
Brock
You have multiple packages dealing with maps. The most easy is maps, which gives you the states map. You can plot the vertices over using the coordinates.
map("state")
points(longitute,latitude)
These plots can be manipulated and added to using the base tools, keeping in mind the x axis is the longitude and the y axis is the latitude. edges can be plotted using the segments() function.
In ggplot2 just use the map_data() function, which gives you the shape-data of the map, and the geom_polygon() to add it to the graph in whatever form you want. Again, you can add the vertices and edges using the coordinates with the appropriate ggplot2 function geom_point() and geom_segment(). The code you link at shows you how, or otherwise look at this for an example.
Next to that, you can take a look at the packages maptools, which offers more functionality and, mapproj, which allows for different projections of the same map. You can use these packages as well to calculate geographical distances in a coordinate system.
mapdata contains more databases, and covers basically the whole world. You can work with coordinates pretty nicely.